Predicting ecosystem productivity based on plant community traits
2022
He, Nianpeng | Yan, Pu | Liu, Congcong | Xu, Li | Li, Mingxu | Van Meerbeek, Koenraad | Zhou, Guangsheng | Zhou, Guoyi | Liu, Shirong | Zhou, Xuhui | Li, Shenggong | Niu, Shuli | Han, Xingguo | Buckley, Thomas N. | Sack, Lawren | Yu, Guirui
With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change.
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